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A whole-school approach to learning for environmental sustainability
Description: This paper addresses the whole-school approach to sustainability by summarizing the latest research and leading experiences with the objective of informing policy development and related activities. It offers …Subject Area: 1. Natural sciences, 2. Engineering and technology, Earth and related environmental sciences, Environmental engineering
Author:
Time to read: 69 min
Date Added: 09-04-2022
DigComp competence area: 2. Communication and collaboration
DigComp competence: 2.4 Collaborating through digital technologies
Green Algorithms: Quantifying the Carbon Footprint of Computation
Description: A methodological framework to estimate the carbon footprint of any computational task in a standardized and reliable way is presented and metrics to contextualize GHG emissions are definedSubject Area: 1. Natural sciences, 2. Engineering and technology, Computer and information sciences, Electrical engineering, electronic engineering, information engineering, Physical sciences
Author: Lannelongue, L., Grealey, J., and Inouye, M.
Time to read: 150 min
Date Added: 06-04-2022
DigComp competence area: 1. Information and data literacy
DigComp competence: 1.3 Managing data, information and digital content
2021 Best Practice Guidelines for the EU Code of Conduct on Data Centre Energy Efficiency
Description: This document is a companion to the EU Code of Conduct on Data Centre Energy Efficiency and provides the full list of identified Best Practices for data centre …Subject Area: 1. Natural sciences, 2. Engineering and technology, Computer and information sciences, Electrical engineering, electronic engineering, information engineering
Author: Acton M., Bertoldi P., Booth J
Time to read: 90 min
Date Added: 01-03-2022
DigComp competence area: 1. Information and data literacy
DigComp competence: 1.3 Managing data, information and digital content
A Methodology for Saving Energy in Educational Buildings Using an IoT Infrastructure
Description: This article describes a methodology for achieving energy savings in schools based on the utilization of data produced by an IoT infrastructure installed inside school buildings and related …Subject Area: 1. Natural sciences, 2. Engineering and technology, Computer and information sciences, Electrical engineering, electronic engineering, information engineering, Systems engineering
Author: Georgios Mylonas, Dimitrios Amaxilatis, Stelios Tsampas, Lidia Pocero
Time to read: 90 min
Date Added: 01-03-2022
DigComp competence area: 1. Information and data literacy
DigComp competence: 1.3 Managing data, information and digital content
Unraveling Green Information Technology Systems as a Global Greenhouse Gas Emission Game-Changer
Description: Green information technology systems (Green ITS) are proposed as a strategy to reduce greenhouse gases (GHGs) emissions and other environmental impacts while supporting ecological sustainable development. The Green …Subject Area: 1. Natural sciences, 2. Engineering and technology, Computer and information sciences, Electrical engineering, electronic engineering, information engineering, Systems engineering
Author: Katundu Imasiku, Valerie Thomas and Etienne Ntagwirumugara
Time to read: 450 min
Date Added: 01-03-2022
DigComp competence area: 1. Information and data literacy
DigComp competence: 1.3 Managing data, information and digital content
The Use of IT Solutions Offered in the Public Cloud to Reduce the City’s Carbon Footprint
Description: An important trend in today’s economy is to reduce the carbon footprint of organizations, businesses and households. Modern technologies, including ICT solutions, contribute to the reduction of CO2 …Subject Area: 1. Natural sciences, 2. Engineering and technology, Computer and information sciences
Author: Tomasz Turek , Damian Dziembek and Marcin Hernes
Time to read: 250 min
Date Added: 28-02-2022
DigComp competence area: 1. Information and data literacy
DigComp competence: 1.3 Managing data, information and digital content
Green AI
Description: Creating efficiency in AI research will decrease its carbon footprint and increase its inclusivity as deep learning study should not require the deepest pocketsSubject Area: 1. Natural sciences, Computer and information sciences
Author: ROY SCHWARTZ, JESSE DODGE, NOAH A. SMITH, AND OREN ETZIONI
Time to read: 150 min
Date Added: 27-02-2022
DigComp competence area: 1. Information and data literacy
DigComp competence: 1.3 Managing data, information and digital content